JPMorgan Will Use AI to Carry Out Trades Across the World
The finance sector is getting more comfortable when it comes to allowing machines to make decisions for themselves, and now the Financial Times reports (paywall) that JPMorgan will use machine learning to perform trades across all of its its global equities algorithms. Instead of relying on hand-coded rules developed by humans, the system, called LOXM, has learned from billions of past transactions how to buy and sell fast and, crucially, at the best price. Trials in Europe showed that it’s “more efficient” than existing systems (read, "it makes more money"). Clearly that’s compelling for JPMorgan, which will now roll out the software in Asia and America. But as we’ve pointed out before, using machine learning approaches to optimize financial transaction is a great idea—until something goes wrong. For now, AI lacks the transparency required to explain to customers why a particular decision was made. And that may not prove too popular when large sums of money are at stake.
Keep Reading
Most Popular
Large language models can do jaw-dropping things. But nobody knows exactly why.
And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.
How scientists traced a mysterious covid case back to six toilets
When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.
The problem with plug-in hybrids? Their drivers.
Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.
Stay connected
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.